題名: A probabilistic perceptron learning algorithm 作者: T. P. Hong;S. S. Tseng
貢獻者: Department of Information Science and Applications
關鍵詞: connectionist model;linearly separable;perceptron;probabilistic perceptron learning;weight vector
日期: 1992
上傳時間: 2009-11-30T08:03:06Z 出版者: Asia University
摘要: A probabilistic perceptron learning algorithm has been proposed here to reduce the computation time of learning. The proposed algorithm is easily programmed and can drastically decrease the time complexity of learning at the expense of only a little accuracy. Experimental results also show this trade-off being worthwhile. Our proposed probabilistic perceptron learning algorithm thus has practical use, especially when the requirement of computational time is critical